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Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A ce...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329320/ https://www.ncbi.nlm.nih.gov/pubmed/37420300 http://dx.doi.org/10.1186/s13046-023-02734-w |
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author | Guan, Jiezhong Xu, Xi Qiu, Guo He, Chong Lu, Xiaoyue Wang, Kang Liu, Xinyu Li, Yuanyuan Ling, Zihang Tang, Xuan Liang, Yujie Tao, Xiaoan Cheng, Bin Yang, Bo |
author_facet | Guan, Jiezhong Xu, Xi Qiu, Guo He, Chong Lu, Xiaoyue Wang, Kang Liu, Xinyu Li, Yuanyuan Ling, Zihang Tang, Xuan Liang, Yujie Tao, Xiaoan Cheng, Bin Yang, Bo |
author_sort | Guan, Jiezhong |
collection | PubMed |
description | BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model. RESULTS: Incorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identified PYGL as a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC. CONCLUSION: PYGL was identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02734-w. |
format | Online Article Text |
id | pubmed-10329320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103293202023-07-09 Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC Guan, Jiezhong Xu, Xi Qiu, Guo He, Chong Lu, Xiaoyue Wang, Kang Liu, Xinyu Li, Yuanyuan Ling, Zihang Tang, Xuan Liang, Yujie Tao, Xiaoan Cheng, Bin Yang, Bo J Exp Clin Cancer Res Research BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model. RESULTS: Incorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identified PYGL as a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC. CONCLUSION: PYGL was identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02734-w. BioMed Central 2023-07-08 /pmc/articles/PMC10329320/ /pubmed/37420300 http://dx.doi.org/10.1186/s13046-023-02734-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Guan, Jiezhong Xu, Xi Qiu, Guo He, Chong Lu, Xiaoyue Wang, Kang Liu, Xinyu Li, Yuanyuan Ling, Zihang Tang, Xuan Liang, Yujie Tao, Xiaoan Cheng, Bin Yang, Bo Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title | Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title_full | Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title_fullStr | Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title_full_unstemmed | Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title_short | Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC |
title_sort | cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker pygl as a therapeutic target for hnscc |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329320/ https://www.ncbi.nlm.nih.gov/pubmed/37420300 http://dx.doi.org/10.1186/s13046-023-02734-w |
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